| Records |
| Author |
Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. |
| Title |
A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning |
Type |
Journal Article |
| Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
| Volume |
520 |
Issue |
1 |
Pages |
1348-1361 |
Keywords  |
astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general |
| Abstract |
Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs. |
| Address |
[Gammaldi, V; Sanchez-Conde, M. A.; Coronado-Blazquez, J.] Univ Autonoma Madrid, Departamentode Fis Teor, E-28049 Madrid, Spain, Email: viviana.gammaldi@uam.es; |
| Corporate Author |
|
Thesis |
|
| Publisher |
Oxford Univ Press |
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0035-8711 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
WOS:000937053400014 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
no |
| Call Number |
IFIC @ pastor @ |
Serial |
5489 |
| Permanent link to this record |
| |
|
| |
| Author |
Trotta, R.; Johannesson, G.; Moskalenko, I.V.; Porter, T.A.; Ruiz de Austri, R.; Strong, A.W. |
| Title |
Constraints on Cosmic-Ray Propagation Models from a Global Bayesian Analysis |
Type |
Journal Article |
| Year |
2011 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
| Volume |
729 |
Issue |
2 |
Pages |
106 - 16pp |
| Keywords |
astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical |
| Abstract |
Research in many areas of modern physics such as, e. g., indirect searches for dark matter and particle acceleration in supernova remnant shocks rely heavily on studies of cosmic rays (CRs) and associated diffuse emissions (radio, microwave, X-rays, gamma-rays). While very detailed numerical models of CR propagation exist, a quantitative statistical analysis of such models has been so far hampered by the large computational effort that those models require. Although statistical analyses have been carried out before using semi-analytical models (where the computation is much faster), the evaluation of the results obtained from such models is difficult, as they necessarily suffer from many simplifying assumptions. The main objective of this paper is to present a working method for a full Bayesian parameter estimation for a numerical CR propagation model. For this study, we use the GALPROP code, the most advanced of its kind, which uses astrophysical information, and nuclear and particle data as inputs to self-consistently predict CRs, gamma-rays, synchrotron, and other observables. We demonstrate that a full Bayesian analysis is possible using nested sampling and Markov Chain Monte Carlo methods (implemented in the SuperBayeS code) despite the heavy computational demands of a numerical propagation code. The best-fit values of parameters found in this analysis are in agreement with previous, significantly simpler, studies also based on GALPROP. |
| Address |
[Trotta, R.] Univ London Imperial Coll Sci Technol & Med, Astrophys Grp, Blackett Lab, London SW7 2AZ, England |
| Corporate Author |
|
Thesis |
|
| Publisher |
Iop Publishing Ltd |
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0004-637x |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ISI:000288608700029 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
541 |
| Permanent link to this record |
| |
|
| |
| Author |
Johannesson, G.; Ruiz de Austri, R.; Vincent, A.C.; Moskalenko, I.V.; Orlando, E.; Porter, T.A.; Strong, A.W.; Trotta, R.; Feroz, F.; Graff, P.; Hobson, M.P. |
| Title |
Bayesian analysis of cosmic-ray propagation: evidence against homogeneous diffusion |
Type |
Journal Article |
| Year |
2016 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
| Volume |
824 |
Issue |
1 |
Pages |
16 - 19pp |
| Keywords |
astroparticle physics; cosmic rays; diffusion; Galaxy: general; ISM: general; methods: statistical |
| Abstract |
We present the results of the most complete scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm, augmented by the BAMBI neural network machine-learning package. This is the first study to separate out low-mass isotopes (p, (p) over bar and He) from the usual light elements (Be, B, C, N, and O). We find that the propagation parameters that best-fit p, (p) over bar, and He data are significantly different from those that fit light elements, including the B/C and Be-10/Be-9 secondary-to-primary ratios normally used to calibrate propagation parameters. This suggests that each set of species is probing a very different interstellar medium, and that the standard approach of calibrating propagation parameters using B/C can lead to incorrect results. We present posterior distributions and best-fit parameters for propagation of both sets of nuclei, as well as for the injection abundances of elements from H to Si. The input GALDEF files with these new parameters will be included in an upcoming public GALPROP update. |
| Address |
[Johannesson, G.] Univ Iceland, Inst Sci, Dunhaga 3, IS-107 Reykjavik, Iceland |
| Corporate Author |
|
Thesis |
|
| Publisher |
Iop Publishing Ltd |
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0004-637x |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
WOS:000377937300016 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
2727 |
| Permanent link to this record |
| |
|
| |
| Author |
AMON and ANTARES Collaborations (Ayala Solares, H.A. et al); Barrios-Marti, J.; Coleiro, A.; Colomer, M.; Gozzini, R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan-Chowdhury, N.R.; Lotze, M.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. |
| Title |
A Search for Cosmic Neutrino and Gamma-Ray Emitting Transients in 7.3 yr of ANTARES and Fermi LAT Data |
Type |
Journal Article |
| Year |
2019 |
Publication |
Astrophysical Journal |
Abbreviated Journal |
Astrophys. J. |
| Volume |
886 |
Issue |
2 |
Pages |
98 - 8pp |
| Keywords |
BL Lacertae objects: general; cosmic rays; gamma-ray burst: general; gamma rays: general; neutrinos |
| Abstract |
We analyze 7.3 yr of ANTARES high-energy neutrino and Fermi Large Area Telescope (LAT) gamma-ray data in search of cosmic neutrino + gamma-ray (nu + gamma) transient sources or source populations. Our analysis has the potential to detect either individual nu + gamma transient sources (durations delta t less than or similar to 1000 s), if they exhibit sufficient gamma-ray or neutrino multiplicity, or a statistical excess of nu + gamma transients of individually lower multiplicities. Individual high gamma-ray multiplicity events could be produced, for example, by a single ANTARES neutrino in coincidence with a LAT-detected gamma-ray burst. Treating ANTARES track and cascade event types separately, we establish detection thresholds by Monte Carlo scrambling of the neutrino data, and determine our analysis sensitivity by signal injection against these scrambled data sets. We find our analysis is sensitive to nu + gamma transient populations responsible for >5% of the observed gamma-coincident neutrinos in the track data at 90% confidence. Applying our analysis to the unscrambled data reveals no individual nu + gamma events of high significance; two ANTARES track + Fermi gamma-ray events are identified that exceed a once per decade false alarm rate threshold (p = 17%). No evidence for subthreshold nu + gamma source populations is found among the track (p = 39%) or cascade (p = 60%) events. Exploring a possible correlation of high-energy neutrino directions with Fermi gamma-ray sky brightness identified in previous work yields no added support for this correlation. While TXS.0506+056, a blazar and variable (nontransient) Fermi gamma-ray source, has recently been identified as the first source of high-energy neutrinos, the challenges in reconciling observations of the Fermi gamma-ray sky, the IceCube high-energy cosmic neutrinos, and ultrahigh-energy cosmic rays using only blazars suggest a significant contribution by other source populations. Searches for transient sources of high-energy neutrinos thus remain interesting, with the potential for either neutrino clustering or multimessenger coincidence searches to lead to discovery of the first nu + gamma transients. |
| Address |
[Solares, H. A. Ayala; Cowen, D. F.; DeLaunay, J. J.; Keivani, A.; Mostafa, M.; Murase, K.; Turley, C. F.] Penn State Univ, Dept Phys, 104 Davey Lab, University Pk, PA 16802 USA, Email: cft114@psu.edu |
| Corporate Author |
|
Thesis |
|
| Publisher |
Iop Publishing Ltd |
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0004-637x |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
WOS:000503245500001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
4227 |
| Permanent link to this record |
| |
|
| |
| Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
| Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
| Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
| Volume |
656 |
Issue |
|
Pages |
A62 - 18pp |
| Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
| Abstract |
Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources. |
| Address |
[Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com |
| Corporate Author |
|
Thesis |
|
| Publisher |
Edp Sciences S A |
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0004-6361 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
WOS:000725877600001 |
Approved |
no |
| Is ISI |
yes |
International Collaboration |
yes |
| Call Number |
IFIC @ pastor @ |
Serial |
5053 |
| Permanent link to this record |
